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Zewen Zhu, Kuai Ye, Xinhua Yu, Zefang Lin, Gangzong Xu, Zhenyou Guo, Shoushan Lu, Biao Nie and Huapeng Chen
The technical condition of bridges has become a crucial issue for organizing the maintenance and repairs in bridge management systems. It is of great practical engineering significance to construct an effective model for predicting the technical conditio...
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Suhee Jo, Ryeonggu Kwon and Gihwon Kwon
GitHub serves as a platform for collaborative software development, where contributors engage, evolve projects, and shape the community. This study presents a novel approach to analyzing GitHub activity that departs from traditional methods. Using Discre...
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Jinqiang Yao, Yu Qian, Zhanyu Feng, Jian Zhang, Hongbin Zhang, Tianyi Chen and Shaoyin Meng
With the development of vehicle-road network technologies, the future traffic flow will appear in the form of hybrid network traffic flow for a long time. Due to the change in traffic characteristics, the current hard shoulder running strategy based on t...
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Chen Zhang, Celimuge Wu, Min Lin, Yangfei Lin and William Liu
In the advanced 5G and beyond networks, multi-access edge computing (MEC) is increasingly recognized as a promising technology, offering the dual advantages of reducing energy utilization in cloud data centers while catering to the demands for reliabilit...
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Frédéric Leroux, Mickaël Germain, Étienne Clabaut, Yacine Bouroubi and Tony St-Pierre
Digital twins are increasingly gaining popularity as a method for simulating intricate natural and urban environments, with the precise segmentation of 3D objects playing an important role. This study focuses on developing a methodology for extracting bu...
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Xinyan Song, Chengyue Wang and Wenxin Liu
Purpose: Improving agricultural carbon-output efficiency is an important path to realize the ?double carbon? goal in the Yellow River Basin. In the context of rapid urbanization development, it is significant to explore whether promoting urbanization wil...
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Ziyi Wang, Xinran Li, Luoyang Sun, Haifeng Zhang, Hualin Liu and Jun Wang
Efficient yet sufficient exploration remains a critical challenge in reinforcement learning (RL), especially for Markov Decision Processes (MDPs) with vast action spaces. Previous approaches have commonly involved projecting the original action space int...
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Jiaming Li, Ning Xie and Tingting Zhao
In recent years, with the rapid advancements in Natural Language Processing (NLP) technologies, large models have become widespread. Traditional reinforcement learning algorithms have also started experimenting with language models to optimize training. ...
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Jin Wang, Peng Zhao, Zhe Zhang, Ting Yue, Hailiang Liu and Lixin Wang
The upset state is an unexpected flight state, which is characterized by an unintentional deviation from normal operating parameters. It is difficult for the pilot to recover the aircraft from the upset state accurately and quickly. In this paper, an ups...
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Mohammed Saïd Kasttet, Abdelouahid Lyhyaoui, Douae Zbakh, Adil Aramja and Abderazzek Kachkari
Recently, artificial intelligence and data science have witnessed dramatic progress and rapid growth, especially Automatic Speech Recognition (ASR) technology based on Hidden Markov Models (HMMs) and Deep Neural Networks (DNNs). Consequently, new end-to-...
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